Two of my favorite blogs — Slate Star Codex (topics: psychiatry, social commentary) and Marginal Revolution (topics: economics, everything else) — have both linked to Karl Friston papers in the last 24 hours. Since one of my bosses is a Friston enthusiast, and he's the only Friston devotee I've ever met, and neither of these blogs has anything to do with what I work on, this gave me a Worlds-Are-Colliding feeling.
A while ago I quoted a paper by Lawson, Rees & Friston about predictive-processing-based hypotheses of autism. They said:
This provides a simple explanation for the pronounced social-communication difficulties in autism; given that other agents are arguably the most difficult things to predict. In the complex world of social interactions, the many-to-one mappings between causes and sensory input are dramatically increased and difficult to learn; especially if one cannot contextualize the prediction errors that drive that learning.
And I was really struck by the phrase “arguably the most difficult thing to predict”. Really? People are harder to predict than, I don’t know, the weather? Weird little flying bugs? Political trends? M. Night Shyamalan movies? And of all the things about people that should be hard to predict, ordinary conversations?
I totally endorse the rest of his post, but here I need to disagree. Other people being the hardest thing to predict seems perfectly reasonable to me. The weather isn't that hard to predict decently well: just guess that the weather tomorrow will be like it is today and you'll be pretty damn accurate. Add in some basic seasonal trends — it's early summer, so tomorrow will be like today but a little warmer — and you'll get closer yet. This is obviously not perfect, but it's also not that much worse than what you can do with sophisticated meteorological modeling. Importantly, the space between the naive approach and the sophisticated approach doesn't leave a lot of room to evolve or learn better predictive ability.
Weird flying bugs aren't that hard to predict either; even dumb frogs manage to catch them enough to stay alive. I'm not trying to be mean to amphibians here, but on any scale of inter-species intelligence they're pretty stupid. The space between how well a frog can predict the flight of a mosquito and how well some advanced avionics system could do so is potentially large, but there's very little to be gained by closing that predictive gap.
Political trends are hard to predict, but only because you're predicting other human agents aggregated on a much larger scale. A scale that was completely unnecessary for us to predict, I might add, until the evolutionary eye-blink of ten thousand years or so ago.
Predicting movies is easier than predicting other human agents, because dramatic entertainments — produced by humans, depicting humans — are just a subset of interacting with other human agents. If you have a good model of how other people will behave, then you also have a good model of how other people will behave when they are acting as story tellers, or when they are characters. (If characters don't conform to the audience's model of human agents at least roughly, they aren't good characters.)
Maybe a better restatement of Friston et al. would be "people are are arguably the most difficult things to predict from the domain of things we have needed to predict precisely and have any hope of predicting precisely."
As an AI researcher, I think I am required to have an opinion about this. Here's what I have to say to the various tribes.
AI-pessimists: please remember that the Luddites have been wrong about technology causing economic cataclysm every time so far. We're talking about several consecutive centuries of wrongness. ((I am aware of the work of Gregory Clark and others related to Industrial Revolution era wage and consumption stagnation. If a disaster requires complicated statistical models to provide evidence it exists, I say its scale can not have been that disastrous.)) Please revise your confidence estimates downwards.
AI-optimists: please remember that just because the pessimists have always been wrong in the past does not mean that they must always be wrong in the future. It is not a natural law that the optimists must be right. That labor markets have adapted in the long term does not mean that they must adapt, to say nothing of short-term dislocations. Please revise your confidence estimates downwards.
Everyone: many forms of technology are substitutes for labor. Many forms of technology are complements to labor. Often a single form of technology is both simultaneously. It is impossible to determine a priori which effect will dominate. ((Who correctly predicted that the introduction of ATMs would coincide with an increase in employment of bank tellers? Anyone? Anyone? Beuller?)) This is true of everything from the mouldboard plough to a convolutional neural network. Don't casually assert AI/ML/robots are qualitatively different. (For example, why does Bill Gates think we need a special tax on robots that is distinct from a tax on any other capital equipment?)
As always, please exercise cognitive and epistemic humility.
Earlier this week Hadley Wickham, Chief Scientist at RStudio, gave a little talk at Booz Allen. He started out in med school, and one of the things that stuck out from his talk was a comparison between being a consulting statistician and taking a medical history. He tells a similar story in this interview:
One of the things I found most useful from med school was we got trained in how to take a medical history, like how to do an interview. Really, there’s a lot of similarities. When you’re a doctor, someone will come to you and say, “I’ve broken my arm. I need you to put a cast on it.” ((During his in-person talk, the patient with the broken-arm-and-cast instead had a cold and wanted antibiotics, which is a better example since the cold is caused by a virus which will be unaffected by the antibiotics.)) It’s the same thing when you’re a statistician, someone comes to you and says, “I’ve got this problem, I need you to fit a linear model and give me a p-value.” The first task of any consulting appointment is to think about what they actually need, not what they think they want. It’s the same thing in medicine, people self‑diagnose and you’ve got to try and break through that and figure out what they really need.
I think this problem comes up in any consulting or contracting environment. As a consultant, should I:
(a) do what my client is asking me to do, or
(b) figure out why they're asking me to do that, and then figure out what they should want me to do, and then convince them that's what they want to do, and then do that thing?
This is pretty routine, and no surprise to anyone who has worked in consulting. Here's why I'm sharing it though. This is from Megan McArdle's discussion of the CMS Inspector General's report on "How HealthCare.gov Went So, So Wrong." ((Which incidentally is something I have spilled a lot of ink about previously.))
The federal government contracting process is insane. [...] A client is a long-term relationship; you want to preserve that. But the federal contracting system specifically discourages these sorts of relationships, because relationships might lead to something unfair happening. (In fact, the report specifically faults CMS for not documenting that one of the people involved in the process had previously worked for a firm that was bidding.) Instead the process tries to use rules and paperwork to substitute for reputation and trust. There’s a reason that private companies do not try to make this substitution, which is that it’s doomed.
Yes, you end up with some self-dealing; people with the authority to spend money on outside vendors dine very well, can count on a nice fruit basket or bottle of liquor at Christmas, and sometimes abuse their power in other less savory ways. But the alternative is worse, because relying entirely on rules kills trust, and trust is what helps you get the best out of your vendors.
Trust is open ended: You do your best for me, I do my best for you. That means that people will go above and beyond when necessary, because they hope you’ll be grateful and reciprocate in the future. Rules, by contrast, are both a floor and a ceiling; people do the minimum, which is also the maximum, because what do they get out of doing more?
Having everything spelled out exactly in contract not only removes trust from the equation, it eliminates the contractor's ability to give you what you need instead of what you originally ask for. It precludes that consultant from exercising their expertise even though that expertise is the very reason they were given a contract in the first place.
Granted, there are some advantages to a consultant only being able to do what they are initially asked to do. Unscrupulous contractors can't use that chain of logic in (b) above to convince the client to do a lot of unnecessary things. But if we don't trust government managers enough to resist that convincing, why should we trust them enough to write up the RFPs and judge proposals and oversee the performance of the contracts in the first place?
I've been consulting less than a year, and I've already been exposed to too many government agencies who are the equivalent of a hypochondriac who stays up all night reading WebMD. "Yes, yes, I understand you have a fever and your neck is stiff, but no, you do not have meningitis... no it's not SARS either... or bird flu." "Yes, I understand you head everyone talking about 'The Cloud,' but no, not every process should be run via Amazon Web Services, and no, you don't need GPUs for that, and no no NO, there is no reason to run a bunch of graph algorithms on non-graph data."
I know plenty about algorithms, and enough about marketing. ((Enough to draw a paycheck from a department of marketing for a few years, at least.)) And despite that, I'm not sure what this headline actually means. It's eye catching, to be sure, but what would marketing to an algorithm look like?
When you get down to it, marketing is applied psychology. Algorithms don't have psyches. Whatever "marketing to algorithms" means, I don't think it's going to be recognizable as marketing.
Would you call what spammers do to slip past your filters "marketing"? (That's not rhetorical.) Does that count as marketing? Because that's pretty much what Gunton seems to be describing.
Setting aside the intriguing possibility of falling in love with an artificial intelligence, the film [Spike Jonez's Her] raises a potentially terrifying possibility for the marketing industry.
It suggests a world where an automated guardian manages our lives, taking away the awkward detail; the boring tasks of daily existence, leaving us with the bits we enjoy, or where we make a contribution. In this world our virtual assistants would quite naturally act as barriers between us and some brands and services.
Great swathes of brand relationships could become automated. Your energy bills and contracts, water, gas, car insurance, home insurance, bank, pension, life assurance, supermarket, home maintenance, transport solutions, IT and entertainment packages; all of these relationships could be managed by your beautiful personal OS.
If you're a electric company whose customers all interact with you via software daeomns, do you even have a brand identity any more? Aren't we discussing a world in which more things will be commoditized? And isn't that a good thing for most of the categories listed?
What do we really care about: getting goods and services, or expressing ourselves through the brands we identify with? Both, to an extent. But if we can no longer do that through our supermarkets or banking, won't we simply shift that focus it to other sectors: clothes, music, etc.
2. Consider that legislation may be an inferior form of law not just recently, or occasionally, but usually. Instead, consider the ideas of Bruno Leoni, which suggest that common law that emerges from individual cases represents a spontaneous order, while legislation represents an attempt at top-down control that works less well.
Both of these stories remind me of a couple of scenes in Greg Egan's excellent Permutation City. Egan describes a situation where people have daemons to answer their video phones that have learned (bottom-up) how to mimic your reactions well enough to screen out personal calls from automated messages. In turn marketers have software that learns how to recognize if they're talking to a real person or one of these filtering systems. The two have entered an evolutionary race to the point that people's filters are almost full-scale neurocognitive models of their personalities.
Updated: I noticed a floating point error when using this that I discuss correcting at the end of this post.
I thought I would post some of the bite-sized coding pieces I've done recently. To lead off, here's Ruby function to find the distance between two points given their latitude and longitude.
Latitude is given in degrees north of the equator (use negatives for the Southern Hemisphere) and longitude is given in degrees east of the Prime Meridian (optionally use negatives for the Western Hemisphere).
include Math
DEG2RAD = PI/180.0
def lldist(lat1, lon1, lat2, lon2)
rho = 3960.0
theta1 = lon1*DEG2RAD
phi1 = (90.0-lat1)*DEG2RAD
theta2 = lon2*DEG2RAD
phi2 = (90.0-lat2)*DEG2RAD
val = sin(phi1)*sin(phi2)*cos(theta1-theta2)+cos(phi1)*cos(phi2)
val = [-1.0, val].max
val = [ val, 1.0].min
psi = acos(val)
return psi*rho
end
A couple of notes:
Everything with val at the bottom is to deal with an edge case that can crop up when you try to get the distance between a point and itself. In that case val should be equal to 1.0, but on my systems some floating-point errors creep in and I get 1.0000000000000002, which is out of range for the acos() function.
This returns the distance in miles. If you want some other unit, redefine rho with the appropriate value for the radius of the earth in your desired unit (6371 km, 1137 leagues, 4304730 passus, or what have you).
This assumes the Earth is spherical, which is a decent first approximation, but is still just that: a first approximation. ((As far as I'm concerned, this is my canonical example of the difference between a first and second approximation. The Earth isn't really a oblate spheroid either, but that makes a very good second approximation — about 100 m. (See John Cook here and here.) ))
I am currently writing a second version to account for the difference between geographic and geocentric latitude which should do a good job of accounting for the Earth's eccentricity. The math is not hard, but finding ground truth to validate my results against is, since the online calculators I've tried to check against do not make their assumptions clear. I did find a promising suite of tools for pilots, and I'd hope if you're doing something as fraught with consequences as flying that you've accounted for these sorts of things.
xkcd #1318 — "Protip: You can win every exchange just by being one level more precise than whoever talked last. Eventually, you'll defeat all conversational opponents and stand alone."
Update:
I've been putting this to use in a new project, and I've noticed an edge case that didn't crop up before. Due to some floating-point oddities, trying to get the distance between a point and itself will throw an error. In that case the value passed to acos() should be 1.0 but ends up being 1.0000000000000002 on my system. Since the domain of acos() is [-1,1] this is no good.
If you want to be on the safe side you can replace this...
val = sin(phi1)*sin(phi2)*cos(theta1-theta2)+cos(phi1)*cos(phi2)
val = [-1.0, val].max
val = [ val, 1.0].min
psi = acos(val)
...and that will take care of things. (Yes, this is a verbose way of doing things, but I often prefer the verbose-and-overt to the laconic-and-recondite.)
Let's put aside how we personally feel about ObamaCare for a moment. Ignore for the time being any considerations of the politics, economics, efficiency, justice, equity, etc. of the law. ((After all, you, dear readers, are strangers to me, and I find it slightly uncivilized to discuss politics, religion or sex with strangers.))
Let's steer far clear of the Knowledge Problem and the Calculation Debate and other perennial political-economic anlages.
Let's not refer to the NHS, or contemplate citations to the Oregon Medicaid Study or the World Health Report 2000.
Let's certainly not contemplate an alethiological analysis of the utterance "If you like your doctor, you will be able to keep your doctor. Period."
I'm going to leave all that stuff off the account while I explain to you why I'm brimming with epicaricacy at the failure of the Healthcare.gov exchange launches.
However, the sub-rational side of me is loving this. Not for any partisan reasons — I'm an "a plague a' both your houses" sort of guy — but rather because it is so satisfying to this geek to see the President, ((This president, no less, so lovingly and recently hailed as "the iPod President.")) his cabinet secretaries, senators, and all the other high and mighty mandarins and viziers of the Beltway brought low before the intransigent reality of Code.
Compilers are even more stubborn than the tide.
All these powerful people are learning (one hopes) the painful lesson that so many powerful people before them have learned when confronting technical problems. It does not matter how many laws you can create with the stroke of your pen, nor how many regiments you can order about, nor how many sheriffs or tax collectors or wardens you direct: you can't give orders to Computers. It is nice to see such mighty people forced to acknowledge — as thousands of hapless executives and others have in the past — that things are not as simple as commanding geeky worker bees to make it so. No number of fiats, from however august an authority, can summon software in to being: It must be made.
As my father — a former legislative assistant on the Hill — said, "passing a law requiring the exchanges to be open is like passing a law forbidding people from being sick, and just as effective."
Compilers don't care about oratory or rhetoric. Political capital can't find bugs. Segfaults aren't fixed at whistle-stops or town-halls or photo-ops. No quantity of arm-bending or tongue-wagging or log-rolling or back-scratching can plug memory leaks. You can't hand-shake or baby-kiss your way into working code.
I tend to see two different mistaken attitudes among non-geeks when it comes to how software is actually made. Some people think it's complete magic, which is flattering but utterly wrong. Others see it as "just pressing buttons," which is wrong but utterly arrogant.
Programmers sit at computers, stare at monitors, and type. Which is exactly what J. Random Whitecollar does, so how hard can it be? It is, after all, "just typing" — although in the same way that surgery is just cutting and stitching. ((One should be as loathe to hire inexperienced coders for mission critical software as one would be to hire a butcher and a tailor to collaborate on an appendectomy.))
I have become accustomed — as every CS grad student becomes — to getting emails from founders seeking technical expertise for their start-ups. The majority of these are complete rubbish, written by two troglodytes who imagine that coming up with an idea plus a clever name for a website constitutes the bulk of the work. These emails typically include a line about "just needing someone to create the site/app/program for us." This is a dead give away that these people will make terrible partners. Just create it? Just? You might as well tell a writer that you have an idea for a novel, and could he please just write the book for you?
Begala's "Stroke of the pen; law of the land; kinda cool" is fine for politics. But when it comes to software this doesn't fly.
This is the same attitude I see from the the White House. Not only did they start off the process with the general suits-vs-geeks attitude, they continued at every turn to place precedence on political desires over engineering realities: failing to set realistic deadlines from the start, leaving all details up to the numerous "the secretary shall determine" clauses in the legislation, delaying the date that states must decide if they would run their own exchanges, delaying finalizing what the rules on the back end would be for insurers, HHS insisting on doing the general contracting itself, ((Yes, really. Because they have so much experience with this sort of thing.)) the head-in-the-sand "brisk management" they engaged in when it became clear the deadline would be slipped, etc., etc. Over and over again the political establishment prioritized their own wants over the engineering needs.
Suits imagine they have the hard job, because that's the only job they know how to do. Yes, the political wrangling is difficult. But we geeks have sat in those frustrating meetings, attempting to get disparate parties on the same page. We've drafted those memos, and written those reports, and had those conference calls. We have to do all that too. When's the last time the suits tried our job? When's the last time they wrestled with memory allocation bug in ad hoc dynamic data structures nested four deep? When have they puzzled out a floating point underflow error? When have they deciphered an undocumented API?
The psychologically easiest response, when confronted with something you have no clue how to do, is to assert that it's simple, and you would easily do it if only you had the inclination and time denied you by having to deal with more rigorous matters.
I don't want to fall in to the opposite trap here of assuming the other guy's job, i.e. the political, non-engineering one, is easy. But let me ask you some questions. How many people in the executive branch have the jobs they do because they donated to a campaign or ran a solid get-out-the-vote drive in a swing state, or did something else politically advantageous to the current occupant of the Oval Office but otherwise entirely unrelated to the department/bureau/administration they now give orders to? And how many political appointees are where they are because they've mastered their craft over tens of thousands of hours of practice?
Now answer those same questions, but substitute "software engineering firm" for "executive branch." What's the ratio of people who get ahead by who-they-know to those who are promoted for what-they-know there? Silicon valley isn't exactly known for sinecures and benefices. On the other hand OPM has entire explicit classes of senior-level officials who are where they are for no other reason than POTUS's say-so. And this isn't some kind of sub-rosa, wink-wink-nudge-nudge thing: this is exactly how the administration is supposed to function.
Let's shift gears and take a look at Charette's (soon-to-be-) classic article, "Why Software Fails." I don't expect the politicians and bureaucrats in charge of this thing to have read K&R or SICP backwards and forwards or have a whole menagerie of O'Reilly books on their shelf. But they at least ought to be familiar with this sort of thing before embarking on a complete demolition and remodel of a sixth of the US economy that was critically dependent on a website.
Here's Charette's list of common factors:
Unrealistic or unarticulated project goals
Inaccurate estimates of needed resources
Badly defined system requirements
Poor reporting of the project's status
Unmanaged risks
Poor communication among customers, developers, and users
Use of immature technology
Inability to handle the project's complexity
Sloppy development practices
Poor project management
Stakeholder politics
Commercial pressures
Let's assume the final one doesn't apply (although I'm sure there were still budget constraints, since I remember multiple proposals all summer and autumn to fix this by throwing more money at it). Other than that, I could find a news story to back up the ObamaCare site making every one of these mistakes other than #7. You're looking at 10 out of 12 failure indicators. Even granting very generous interpretation of events there's no way the Exchanges weren't dealing with at the very least #1, 3, 4, and 6.
I've seen plenty of people on the Right gleefully jeer that this is what happens when you don't have market incentives to guide you. They're right.
I've also seen plenty of people on the Left retort that history is littered with private enterprises that have wasted billions on poorly-executed ambitious IT projects. They're right too.
Of course, they're both wrong as well.
The people on the Right are engaging in a huge amount of survivorship bias. All those companies that screwed up an IT rollout like this aren't around for us to notice anymore. Maybe they aren't bankrupt, but they're not as salient as their successful competitors either. Failures are obscure, successes are obvious.
The people on the Left are misunderstanding how distributed, complex systems like a market work. Yes, individual agents will fail. That's part of the plan, just like it is in evolution. You can't have survival-of-the-fittest without also having the contrapositive. ((ahem *bailouts* ahem!)) We don't have the freedom to develop healthcare.gov via the distributed market-driven exploration process. All of our eggs are in this one basket.
I don't think the people making either claim really grok how a market is supposed to operate. It wouldn't help to give the healthcare.gov developers an equity stake or pay them lavish bonuses. You might get more effort from them or a better group of programmers, but you've still only got a single attempt at getting this right. And the people pointing out all the wasted private-sector IT spending are also missing the point. Yes, there are failures, but the entire system relies on failures to find the successes. The ACA does the opposite of that by forcing everyone to adopt the same approach and continuing to disallow purchasing across state lines. That's a recipe for catastrophic loss of diversity and dampening of feedback signals.
I've seen people on all sides suggest that what we really needed to do was go to Silicon Valley and hire some hotshot programmers and give them big paychecks, and they could build this for us lickety-split. Instead, we're stuck paying people mediocre GS salaries (or the equivalent via contractors), so we get mediocre programmers who deliver mediocre product. I don't think this reasoning holds up. Another common observation, which I also think is flawed, is almost the opposite: there was never a way to make this work since good coders in the Valley expect to get equity stakes when they create big, ambitious software products, and no such compensation is possible for a federal contract.
At the margin more money will obviously help. Ceteris paribus, you will get more talented people. But that's not the whole story, by a long-shot.
1. There's several orders of magnitude between the best programmers and the median programmers. You can't even quantify the difference in quality between the best and the worst, because the worst have negative productivity: they introduce more bugs into the code than they fix. Paying marginally more may get you marginally better coders, but there's a qualitative difference between the marginally-above-average and the All Stars.
2. The way you get the best is not often by offering more money. It helps, it's only a piece of the whole story. The way you get the best is by giving them interesting problems to work on.
3. The exchange is not an interesting problem. In fact it's quite the opposite. It's almost entirely what Eric S Raymond calls "glue" — it pastes a bunch of other systems together, but doesn't do anything very interesting on its own. ESR cautions programmers (quite rightly!) to use as little glue as possible. Glue is where errors — and madness — insinuate themselves in to a project. ((See Eric S Raymond, "The Art of Unix Programming," 2003. This may be a little advanced for a legislator or administrator to read, but is is that much to ask that the people governing these critical systems learn a little but about how they work?))
This is related to all of the discussion I've heard about how Obama got geeks to volunteer to help him create various tools for his campaigns. If hotshot programmers would do that, the thinking goes, why wouldn't they pitch in to build an awesome exchange?
Simple: because the exchange is boring. It's as bureaucratic as it comes. Working on it would require a massive amount of interfacing with non-technical managers in order to comply with non-trivial, difficult-to-interpret legislative/regulatory rules. Do you know how many lawyers a coder would have to talk to in order to manage a project like this?! Coders are almost as allergic to lawyers as the Nac Mac Feegle are.
All that managerial overhead is no fun at all, especially compared to the warm-and-fuzzies some people feel when they get to participate in the tribal activity of a big election. ((Is it Robin Hanson who has the theory about political engagement being another form of team sport and spectation?))
Not only is building the exchanges not fun compared to building a campaign website, but it comes with all sorts of deadlines and responsibilities too. If you think up some little GPS app to point people toward their polling place, but it doesn't work the way you want, or handle a large enough load... no sweat. It was a hobby thing anyway. If it works then you feel good about helping to get your guy elected. If it doesn't then you just move on to the next hobby that strikes your fancy.
Was there a way for the Obama administration to harness some of that energy from the tech community? Yeah. Could they have used open source development to make some of the load lighter? Yeah. But it's no cure-all. At the end of the day there was a lot of fiddly, boring, thankless, unsexy government work to be done.
Let's take a slight detour and discuss Twitter. A professor I know claims that several bad months of performance by healthcare.gov is no big deal. After all, Twitter used to be plagued by the Fail Whale but it's a very successful enterprise now.
First of all, they're the exception. People remember the Fail Whale specifically because Twitter is the opposite of a failure now.
Secondly, tweeting is entertaining. Buying insurance isn't. People will put up with more hurdles being put between them and free fun than between them and expensive drudgery.
Thirdly, Twitter never had to worry about its delicate actuarial calculus being thrown off by a non-random sample of users pushing their way through a clogged system.
Fourthly, if Twitter screwed something up all its users were free to walk away — either until things were fixed, or forever. We don't have that option w/r/t healthcare.gov.
The administration's responses in the last few weeks to the ongoing troubles have been characterized as "legislation by press release." Let's put aside the constitutional/philosophical issue of whether the President is merely tweaking the way a law is executed, as is his wont, or is re-writing the law of the land by presidential motu propio.
I want to point out that this is another area where comparison to Amazon, Netflix, etc. falls short. If Twitter finds out that some part of their design is unimplementable they have complete prerogative to change the design of their service in any way. They can re-write their ToS or feature list or pricing structure however they want, whenever they want. The State utterly lacks such range of motion and nimbleness. There is thus even less point in people on either the Red Team or Blue Team saying "well the private sector builds massive IT projects all the time." They aren't playing the same game.
Jay Carney et al. have been insisting all along that everything is working (or will be working, or should have been working, or whatever the line is today), and the only problem is it's a bit slow, as if this is a trivial matter. I don't think people realize how relentlessly commerce websites are engineered to remove all the slowness. And I mean all the slowness. Every millisecond of delay costs you sales. Every slowdown lowers your conversion rate. Tens of milliseconds are a big deal. ((And for context, conscious thought is best described on a scale of hundreds of milliseconds, so delays that are nearly too brief to perceive lower you chance of completing a transaction by a noticeable amount.)) Having delays delays measures in minutes is unspeakably bad. Delays in the hours are no longer "delays" — they mean the system doesn't work.
(If you don't believe me then you can do a little experiment. If you're using Chrome, open up a new tab, then go to View > Developer > Developer Tools and click on the Network tab. [I know other browsers have a similar function, but I don't remember what they call it off the top of my head.] Once you see that, go back to the tab you just opened and load www.amazon.com. You'll see all the various files needed to display their page listed in the timeline. Note that the "latency" column is measured in milliseconds. If delays of several minutes were just part of doing business, this isn't how developers would want something reported.)
(Update: here's a look at what the exchange sales funnel actually looks like. Not good, especially for the unsubsidized consumers. And considering this is a product we're required to buy. [How well would Amazon do if they had the IRS requiring you to buy books every year in the name of increased national literacy?] Oh, and considering we don't know who will actually end up paying their bills. And is anyone else a little suspicious at how hard it is to get these numbers? What happened to all the promises of freely shared government data from "the most transparent administration ever"? How does that mesh with not releasing how many people have actually purchased a plan?)
Healthcare.gov sales funnel
These lengthy delays are actually worse than the exchanges not working at all. We'd be better off if they never opened. The healthy kid who's buying a policy because he's told he has to is going to be put off by these delays, but the sick old-timer with diabetes and a bad hip isn't. So rather than not getting any customers, you're getting just the expensive ones. (I feel like we need a sound effect or musical theme to play when the Death Spiral is about to come on stage. Maybe something from "Mars, Bringer of War"?)
This all leads us to Brisk Management and Failing on Time. These are very important engineering management concepts. This post is already dragging on much to long, so I'll summarize in one sentence: it is a huge mistake to take on extra risks just to hit an arbitrary calendar deadline. Or if you'd prefer a sentence with more imagery: it's better that a building take longer to finish than have it done on time but collapse later. The health exchanges look like a textbook case of Failing on Time. Obama was reassuring everyone that signing up was going to be just like shopping on Amazon or Kayak a week — one week! — before the missed launch date. The first missed launch date, that is.
Many of the problems of the exchange implementation were apparent even on paper, in the planning stages. For instance: just how is healthcare.gov supposed to calculate subsidies? That will require a real-time verification of your income. From whence will this information come? The IRS knows a scary amount about us, but it doesn't know until deep into next year how much you made this month. They don't have some server with an API standing by to answer queries like getCurrentIncome(<SSN>). ((If you don't believe me then you should have been around when I was trying to convince Sallie Mae and the Department of Education of my family's correct income was so they could calculate our loan repayments. It took about nine months to convince them that my wife, a teacher, is paid 10 months a year and as a result you can't just multiply her biweekly wages by 26 to get annual income. There are four million teachers in the US, so it's not exactly like this was some rare exception they had to cope with. I wish there was some IRS system for quickly verifying income, because it would have saved me most of a year of mailing in pay stubs and 1040s and W-2s and offer letters and triplicate forms, by which point, of course, the information was out of date and we had to start over.
Sorry to get off on a tangent here, but the federal government is so bad at technology I just can't let this go. And actually, it's not much of a tangent when you consider it was the PPACA that spearheaded the semi-nationalization of the student loan industry. (Drat. I need a footnote for this footnote. A couple of the very important concepts you can learn from "The Art of Unix Programming" (note 7 supra) are the principles of Compactness and Orthogonality. Both of these, and particularly the latter, should be rules for legislation as well. Folding student loan reform into the PPACA in order to game the CBO scoring is a pretty clear violation of both of these principles.)
Compared to health insurance, a student loan is a pretty simple thing. Have you had to deal with studentloans.gov? It's atrocious. Recently they changed the repayment plan that my wife was on without notifying us. That's bad enough. The ugly part is that when they do that, they don't change the displayed label on your account that tells you which plan you're in, so even if you proactively check for changes you won't find out. And the truly hideous thing is that they don't change the label on the info screens that their own representatives can see either, so if you call to verify you still won't find out! It's true that dealing with the banks before was a complete mess, but I chalk that up to the absence of a right-of-exit for consumers. That was bad enough then, but post-nationalization I'm really over a barrel.
Getting people signed up is only the first skirmish for healthcare.gov. All these sorts of ongoing problems, such as the ones I've experienced with student loans, will constitute the bulk of the IT battle, and they have not yet even begun to show up yet.)) So it was pretty inevitable that this feature would be abandoned in favor of the honor system. Which is unfortunate, because I remember ObamaCare supporters swearing up and down that it was completely absurd for their opponents to raise concerns about people hustling the system for subsidies they didn't qualify for. (Not to mention the equivalent assumptions the CBO was forced to make.)
This post is already orders of magnitude longer than I expected, so I'm going to toss in a handful of links to a couple of other people's posts without comment. There were many, many more I could put here, but keeping track of all the ink spilled on this is impossible.
The last four are by Megan McArdle, who is not only one of the most cogent econ-bloggers out there, she also worked as an IT consultant, so she has had a lot of valuable perspective to contribute.
I'll close with this, from Ellen Ullman's excellent memoir Close to the Machine. Ullman was (is?) a card-carrying communist. I mention that so you know she's no anti-government right-wing Tea Party ideologue. This passage describes her experience in the early 90s as the lead developer on a San Francisco project building a computer system to unify all the city's AIDS-related efforts. She started the project over-joyed to be working for "the good guys" instead of some profit-maximizing robber barons, but very quickly it turns in to this:
Next came the budget and scheduling wrangles. Could the second phase be done in December? At first I tried what may be the oldest joke known to programming managers—"Sure you can have it in December! Of What year?"—but my client was in deadly earnest. "There is a political deadline," they said,"and we can't change it." It did no good to explain that writing software was not a political process. The deed was done. They had gone around mentioning various dates—dates chosen almost at random, imagined times, wishes—and the mentioned dates soon took on an air of reality. To all the world, to city departments and planning bureaus, to task forces and advisory boards, the dates had become expectations, commitments. Now there was no way back. The date existed and the software would be "late." Of course, this is the way all software projects become "late"—in relation to someone's fantasy that is somehow adopted as real—but I didn't expect it so soon at the AIDS project, place of "helping people," province of "good."
I asked, "What part of the system would you like me not to do?"
"You tell us," they said.
"This one. This piece here can't be done on time."
"But we must ace that one! It's a political requirement."
Round and round: the same as every software project, any software project. The same place.
